Recent work [1]}, [2]} has revealed limitations in the current methods caused by the inherent ambiguity of the disentanglement objective. They have pointed out the need for equipping models with inductive biases appropriate to their respective application. An example disentanglement task with such increased specificity is the learning to generate multi-object scenes whereby the representation is trained to factorize along object lines [3]}, [4]}, [5]}.
